SUMMARY Surgical site infections account for approximately 20% of the 1.7 million healthcare acquired infections annually. Reprocessing of surgical equipment is essential for avoiding HAIs, yet 1 in 3 hospitals have reprocessing deficiencies and high-profile failures continue. Sterile processing departments (SPDs) are central to surgical performance, and achieving reliable sterile processing is important for the AHRQ Patient Safety Portfolio, yet there is paucity in improvement or systems research in this area. Tasks, technologies, people, internal environments, organization and external environments all need to be harmonized to optimize the system of work. We propose to use Work Systems Analysis (WSA) - an analytical process which models whole systems of work ? combined with the Systems Engineering Initiative for Patient Safety (SEIPS) framework to initiate a major program of research and improvement in sterile processing. Few research projects have ever explored sterile processing as a work system; this project further develops the use of WSA for improvement in healthcare; and will be delivered by a team staff, administrators and embedded human factors specialists. Preliminary studies have revealed a range of socio-technical systems challenges related to safety and quality such as sharps injury risks, complex equipment hides soiling, and dried blood preventing disassembly. The first aim will be to conduct a work systems analysis of two sterile processing departments in one hospital system. Basic process mapping and task analysis will be conducted using interviews, direct observations, photos and videos, instrument tracking data, administrative data, meeting minutes, standard operating procedures, and regulatory documentation. The SEIPS framework will provide a structure in which to organize components of the process into an abstraction hierarchy, which will provide a multi-level model of the interactions between components. A variance matrix will then be produced detailing sources of variation and potential controls for each component. The second aim will be to conduct an exploratory statistical analysis using a variety of administrative and electronic data sources to reveal significant relationships between external outcome measures (bioburden, broken instruments, SSIs), external variances (surgical specialty, operative type, caseload), internal outcome measures (re-work rates, processing times), and internal variances (workforce level, condition of returning trays). A working group will help define hypotheses to test and assure data quality, while the identification of index operations to study will help to control for confounds. The final exploratory aim will be to observe and record changes in the two SPD units over the year duration of the project, and to uncover potential interventions for future interventional studies.